1 Distance Analysis

Load points CSV and plot. Then calculate pairwise geographic distances.

1.1 Adjoin Data sheet and scan sheet - 21AUG22

Load cleaned CSVs

dm<-read.csv("/Users/Kaushiknarasimhan/Dropbox/Phd-MacBook Pro/Ch3/full distance matrix.csv")%>%
  select(1:3)
d<-read.csv("~/Dropbox/Phd-MacBook Pro/Ch3/CH3 analysis/DataSheetPreScan.csv")
s<-read.csv("~/Dropbox/Phd-MacBook Pro/Ch3/CH3 analysis/Scans.csv")%>%
  select(!c(OCR, StdDev:MaxThr))

1.2 Join based on ID tag numbers and write to csv

full_join(d,s,by=c("Trimmed"="M3"))%>%
select(!starts_with("X"))%>%
select(!c(Seq.Ord:Esp))%>%
  mutate(Block=as.numeric(str_match(Trimmed,"B(\\d++)")[,2]),#split block,adult,soil
         Mother=as.numeric(str_match(Trimmed,"A(\\d++)")[,2]),
         Soil=as.numeric(str_match(Trimmed,"S(\\d++)")[,2]),
         Alive=if_else(is.na(altura..cm.),0,1),
         Alive=as.factor(Alive))%>%
  relocate(Block:Alive,.after= Trimmed)%>%
left_join(dm)%>%
  select(!starts_with("X"))%>%
  select(!c(Raices.en.Ctab.,Scan.,En.bolsa.,Horno..,Scan.Name))%>%
  filter(!is.na(Mother))%>%
  mutate( Mother=as.factor(Mother),
          Soil=as.factor(Soil),
          Block=as.factor(Block))%>%
  rename(Stem.Diameter=`diámetro..mm.`,
         Stem.Height=`altura..cm.`,
         WW.above=Peso.Encima,
         WW.below=Peso.Abajo)%>%
  relocate(all_of(c("Dead.Muerta","Germinado.","NOTAS","Notes")),.after= Distance)%>%
  view()->Master

#write.csv(Master,file = paste0("WithScans",Sys.time(),".csv"))

2 Descriptive stats

  Master%>%filter(Alive==1)%>%
  summarise(n())
##    n()
## 1 1270

1270 germinated seeds that were harvested. What is the distribution of seeds that have dry measurements? Looks like blocks 2-7 and 10 are fine. 183 samples were burnt.

##   n()
## 1 183

2.0.1 Table of Mean and Sd of growth metrics by Mother

Mother Stem.Diameter_mean Stem.Diameter_sd Stem.Height_mean Stem.Height_sd WW.below_mean WW.below_sd WW.above_mean WW.above_sd DW.above_mean DW.above_sd DW.below_mean DW.below_sd Area_mean Area_sd Distance_mean Distance_sd SurvRate_mean SurvRate_sd
1 3.696 0.738 3.831 0.721 2.708 0.300 1.076 0.386 0.206 0.092 0.861 0.204 1.927 0.959 1224.850 840.129 0.2857143 0.1511858
2 4.151 0.814 4.393 1.328 3.178 0.444 1.508 0.613 0.282 0.126 1.123 0.141 2.483 1.099 1527.224 1001.414 0.4600000 0.2097618
3 4.865 0.455 5.278 1.078 3.972 0.587 2.266 0.865 0.406 0.181 1.335 0.294 4.235 1.890 1363.799 852.154 0.4571429 0.1554858
4 6.248 0.734 6.959 0.838 7.613 0.630 4.304 1.040 0.816 0.232 2.719 0.299 8.038 2.101 1455.913 977.312 0.6866667 0.1597617
5 6.971 0.461 7.843 0.873 7.416 0.699 5.552 0.919 1.119 0.194 2.352 0.300 10.917 1.949 1504.343 834.839 0.8666667 0.1046536
6 6.319 0.594 7.217 0.697 5.549 0.507 4.125 0.834 0.832 0.220 1.591 0.221 8.135 2.091 1171.965 787.764 0.5933333 0.2218966
7 4.919 0.550 5.295 0.756 4.656 0.443 2.291 0.754 0.412 0.134 1.541 0.184 3.921 1.503 1285.652 870.664 0.7200000 0.1971222
8 6.338 0.784 6.714 1.726 7.471 0.593 4.453 1.129 0.906 0.229 2.478 0.306 8.290 2.681 1125.899 609.388 0.6733333 0.2086236
9 6.040 0.650 6.683 0.938 6.538 0.580 3.721 0.979 0.773 0.301 2.220 0.356 6.766 2.379 1118.418 429.208 0.7733333 0.1579632
10 6.096 0.815 6.441 0.749 6.395 0.813 3.676 1.040 0.683 0.193 2.111 0.294 6.690 2.095 1504.942 1055.760 0.7000000 0.2236068
11 5.531 0.809 5.944 1.333 6.274 0.949 3.099 1.056 0.620 0.326 2.149 0.488 5.633 2.323 1379.354 973.555 0.4466667 0.2199567
12 5.168 0.862 5.758 0.745 5.195 0.721 2.679 0.871 0.519 0.187 2.008 0.310 4.579 1.490 1196.299 631.776 0.6266667 0.1791514
13 7.167 0.662 7.704 0.474 7.224 0.665 5.287 0.846 1.096 0.254 2.319 0.265 10.438 2.204 1447.049 921.030 0.7000000 0.1195229
14 5.543 0.887 5.740 0.727 5.063 0.514 2.719 0.899 0.532 0.198 1.620 0.420 5.043 2.442 1410.901 1040.914 0.3000000 0.1568929
15 4.473 1.162 4.830 1.435 4.042 1.815 2.043 1.864 0.364 0.325 1.421 0.382 3.940 4.112 1551.922 965.868 0.2642857 0.1336306

3 Mother charts

3.0.1 Total Biomass and Mean Total Biomass with self highlighted

Looks like the same pattern as before. Def some variation between mothers

3.0.2 Mean Survival rate

3.0.3 Wet above and below ground biomass

3.0.4 Dry above and below ground biomass

4 Soil charts

4.0.1 Total Biomass and Mean Total Biomass with self highlighted

Soil appears to have more of an effect when accounting for biomass

4.0.2 Mean Survival rate

4.0.3 Wet above and below ground biomass

4.0.4 Dry above and below ground biomass

5 Block charts

5.0.1 Total Biomass and Mean Total Biomass with self highlighted

Soil appears to have more of an effect when accounting for biomass

5.0.2 Mean Survival rate

6 Correlations

6.0.1 Tile plot of Mother vs. Soil

Nothing pops out to me here.

6.0.2 Correlation plot

6.0.3 NMDS of three conditions

6.0.4 Info on the PCAS

7 Models

8 What about Self vs other?

Eck had a categorical variable with either “Seeds in Maternal soil” and “seeds not in maternal soil”. She used block, maternal id and soil id as random variables. I did that here, but does it make sense?